1. 09/05/2019
P-REACT
Video Analytics

2. 09/05/2019
Video Analytics
Analytics using and RGB/IR sensor and an odroid-XU3 system.
Extract salient regions using:
Frame differencing
𝐷 𝑓 =| 𝐼 𝑓 − 𝐼 𝑓−𝑠 |
Morphological filtering (erosion)
𝐷 𝑓 = 𝐷 𝑓 ⊖𝐻
Contour extraction
Accurately detect motion (also tested with IR and depth data)

3. Detect anomalous activity (running, fighting, bag snatching)
09/05/2019
Video Analytics
Quantize each contour with a grid
Form mid-term point trajectories using optical flow
𝜕𝐼 𝜕𝑥 𝑑𝑥 𝑑𝑡 + 𝜕𝐼 𝜕𝑦 𝑑𝑦 𝑑𝑡 + 𝑑𝐼 𝑑𝑡 =0
Extract motion histogram per cell
Use SVM or RT for classification
Aggregate overall cell
Apply temporal smoothing
Detect anomalous activity (running, fighting, bag snatching)

4. Multiple humans tracking and identification
09/05/2019
Video Analytics
Dynamically update background
Divide frame in a grid
Compute foreground change rate per cell
𝜌= 𝑓 𝑖 ∩ 𝑓 𝑖−1 𝑓 𝑖 ∪ 𝑓 𝑖−1
Detect static changes in the background (applied to graffiti detection)
Use pedestrian detection algorithm
Point trajectories connect temporally distant detections
Remove false positives
𝑚𝑖𝑛𝑖𝑚𝑖𝑧𝑒 𝑥 𝑇 𝐴𝑥+ 𝜆 𝑐 𝑇 𝑥
Use gait descriptors for identification
Multiple humans tracking and identification

5. Video Analytics Detection of events
09/05/2019
Video Analytics
Detection and tracking of individuals
Close, mid and far-distance views
Different profiles
Track joiner for enhanced reliability
Detection of events
“Motion”, “Running”, “Chasing”, “Fighting”, “Group”

6. Depth Analytics Analytics using a depth sensor and a NUC system
09/05/2019
Depth Analytics
Analytics using a depth sensor and a NUC system
Extract foreground using depth data
Compute 4D normal vectors
𝑆 𝑥,𝑦,𝑧,𝑡 =𝑓 𝑥,𝑦,𝑡 −𝑧=0
𝒏=𝛻𝑆=( 𝜕𝑓 𝜕𝑥 , 𝜕𝑓 𝜕𝑦 , 𝜕𝑓 𝜕𝑡 ,−1)

7. Accurately detect motion and abnormal incidents (e.g. fighting)
09/05/2019
Depth Analytics
Divide the depth stream in spatio-temporal cells
Project normal vectors on each cell 𝒑 𝒊
𝑐 𝒏 𝑗 , 𝒑 𝑖 =max(0, 𝒏 𝑗 𝑇 𝒑 𝑖 )
Extract HON4D descriptor
Pr 𝒑 𝑖 𝑁 = 𝑗∈𝑁 𝑐 𝒏 𝑗 , 𝒑 𝑖 𝑝 𝑣 ∈𝑃 𝑗∈𝑁 𝑐 𝒏 𝑗 , 𝒑 𝑣
Use Random Trees for classification
Accurately detect motion and abnormal incidents (e.g. fighting)

8. 09/05/2019
Contact Points
CERTH:
Dr. Dimitrios Tzovaras,
Mr. Georgios Stavropoulos,
Dr. Nikolaos Dimitriou,
VICOMTECH:
Mr. Juan Arraiza Irujo,
Dr. Marcos Nieto,